Files
FastDeploy/paddle2onnx/mapper/tensor/scatter.cc
Jason 6343b0db47 [Build] Support build with source code of Paddle2ONNX (#1559)
* Add notes for tensors

* Optimize some apis

* move some warnings

* Support build with Paddle2ONNX

* Add protobuf support

* Fix compile on mac

* add clearn package script

* Add paddle2onnx code

* remove submodule

* Add onnx ocde

* remove softlink

* add onnx code

* fix error

* Add cmake file

* fix patchelf

* update paddle2onnx

* Delete .gitmodules

---------

Co-authored-by: PaddleCI <paddle_ci@example.com>
Co-authored-by: pangyoki <pangyoki@126.com>
Co-authored-by: jiangjiajun <jiangjiajun@baidu.lcom>
2023-03-17 10:03:22 +08:00

78 lines
2.8 KiB
C++

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle2onnx/mapper/tensor/scatter.h"
namespace paddle2onnx {
REGISTER_MAPPER(scatter, ScatterMapper)
int32_t ScatterMapper::GetMinOpset(bool verbose) {
if (!overwrite_) {
Logger(verbose, 16) << "When overwrite is False, " << RequireOpset(16)
<< std::endl;
return 16;
}
Logger(verbose, 11) << RequireOpset(11) << std::endl;
return 11;
}
void ScatterMapper::Opset11() {
auto input_x_info = GetInput("X");
auto input_ids_info = GetInput("Ids");
auto input_updates_info = GetInput("Updates");
auto output_info = GetOutput("Out");
std::string ids_node = helper_->AutoCast(
input_ids_info[0].name, input_ids_info[0].dtype, P2ODataType::INT64);
std::vector<int64_t> shape_val = {input_ids_info[0].shape[0], 1};
std::string shape_node =
helper_->Constant(GetOnnxDtype(P2ODataType::INT64), shape_val);
auto reshape_index_node =
helper_->MakeNode("Reshape", {ids_node, shape_node});
if (!overwrite_) {
auto shape_node = helper_->MakeNode("Shape", {input_x_info[0].name});
std::string zeros_like_node = helper_->ConstOfShape(
shape_node->output(0), GetOnnxDtype(input_x_info[0].dtype),
static_cast<float>(0));
auto scatter_nd_node = helper_->MakeNode(
"ScatterND", {zeros_like_node, reshape_index_node->output(0),
input_updates_info[0].name});
AddAttribute(scatter_nd_node, "reduction", "add");
std::string zero_node = helper_->Constant(
{1}, GetOnnxDtype(input_x_info[0].dtype), static_cast<float>(0));
auto equal_node =
helper_->MakeNode("Equal", {scatter_nd_node->output(0), zero_node});
std::string condition_node = helper_->AutoCast(
equal_node->output(0), P2ODataType::INT64, P2ODataType::BOOL);
helper_->MakeNode("Where", {condition_node, input_x_info[0].name,
scatter_nd_node->output(0)},
{output_info[0].name});
} else {
auto node = helper_->MakeNode(
"ScatterND", {input_x_info[0].name, reshape_index_node->output(0),
input_updates_info[0].name},
{output_info[0].name});
}
}
} // namespace paddle2onnx